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gclmgclm/super-stack/skills/core/frontend-refactor/SKILL.md

frontend-refactor

Skill0 starsChanged 7 months agoMITView on GitHub

Refactor frontend code by separating structural cleanup, UI consistency, state flow, and verification instead of mixing visual edits with risky behavior changes.

We split this skill into the rules it gives an agent

8 rules. About 0 are common, 7 are distinctive, and 1 is very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈7

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 1

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    Use this skill when a frontend change is larger than a simple bugfix and the real goal is to improve maintainability, consistency, or …

    line 8
  2. Distinctive:

    keep behavior changes explicit

    line 22
  3. Distinctive:

    leave behind clearer UI patterns instead of one-off edits

    line 24
  4. Distinctive:

    avoid generic AI-looking visual output when the task includes meaningful UI polish or visual cleanup

    line 26
  5. Distinctive:

    When visual polish matters, choose an explicit visual direction instead of defaulting to generic app UI.

    line 35
  6. Distinctive:

    Keep motion sparse but meaningful.

    line 37
  7. Distinctive:

    Verify both UI structure and the most important user flows after each slice.

    line 39
  8. Very specific:

    Read references/refactor-slices.md when you need a more explicit slicing strategy.

    line 41

≈ “Common” is an estimate: at least 1 in 5 of the 308,232 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

Frontend Refactor

Use this skill when a frontend change is larger than a simple bugfix and the real goal is to improve maintainability, consistency, or interaction quality without losing existing behavior.

Read First

  • docs/overview/roadmap.md and harness/state.md if they exist
  • harness/history.md if it exists
  • docs/reference/conventions.md if it exists
  • the closest layout, state, and routing files involved
  • any existing design or product notes that constrain the refactor
  • references/refactor-slices.md when the work needs safer slicing

Goals

  • separate structural refactor from incidental redesign
  • keep behavior changes explicit
  • improve consistency across layout, state, styles, and reusable components
  • leave behind clearer UI patterns instead of one-off edits
  • preserve the difference between reusing a reference project's structure and copying its implementation
  • avoid generic AI-looking visual output when the task includes meaningful UI polish or visual cleanup

Steps

  1. Define the refactor target.
  2. Identify what must stay behaviorally stable.
  3. Decide whether the task is reusing information architecture, interaction structure, implementation details, or some combination.
  4. Split the work into safe slices instead of rewriting everything at once.
  5. Refactor shared patterns first when multiple screens repeat them.
  6. When visual polish matters, choose an explicit visual direction instead of defaulting to generic app UI.
  7. Make typography, spacing, color, hierarchy, and background treatment intentional rather than leaving them as framework defaults.
  8. Keep motion sparse but meaningful; avoid filler animation.
  9. For validation samples, prefer maintainable skeletons and debug-friendly structure over premature visual fidelity, but do not accept obviously bland or placeholder-looking UI when presentation is part of the task.
  10. Verify both UI structure and the most important user flows after each slice.

Read references/refactor-slices.md when you need a more explicit slicing strategy.

Output

Report:

  • refactor scope
  • stable behavior constraints
  • reference reuse boundary chosen
  • visual direction chosen when relevant
  • shared patterns extracted
  • risky areas
  • verification evidence

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